Data Structures & Algorithms (Midterm Study)
Exam Review | A+ Verified Answers
What are the Software Development Life Cycle Models? - ANSW Waterfall
Agile
Spiral
V-Model
DevOps
List steps in waterfall model - ANSW 1. Analysis
2. Requirements specification
3. Design
4. Implementation
5. Testing and integration
6. Operation and maintenance
List components of technical documentation - ANSW 1. Hierarchical diagram / structure
chart
2. Procedure specification
3. Program listing
4. Test cases
6. Major problems encountered
7. Limitation of current works
What are the 3 Design strategies - ANSW 1. Top-down design
2. Bottom-up design
3. Stepwise refinement
What are the 3 types of parameters? - ANSW 1. Input parameters
2. Output parameters
3. Input-output parameters
What are the two types of testing (Include what they're also known as)? - ANSW 1.
Black-box (Function Testing)
2. White-box (Structural Testing)
Define Algorithm - ANSW A set of instructions for solving a problem in a finite number
of sets
Define Program - ANSW A particular implementation of an algorithm in a chosen
program language
, Algorithm analysis approaches - ANSW 1. Assess time and space recourse
requirements
2. Quantitative comparison (# of operations)
3. Best case, worst case, and average case analysis
4. Lower bound theory
5. Theory of NP-hard and NP-Complete
What is complexity? - ANSW The measure of how resource requirements of a program
or algorithm SCALE (time and space)
What are the typical growth rate functions (8 covered in notes) in order from most
efficient to least efficient? - ANSW 1. 1
2. log n
3. n
4. n log n
5. n^2
6. n^3
7. 2^n
8. n!
What are the two classes of algorithms based on growth rates? - ANSW 1. Polynomial-
time
2. Exponential-time
What are the 6 polynomial-time algorithms? (Bounded by polynomial in n degree) -
ANSW 1. Constant O(1)
2. Logarithmic O(log n)
3. Linear O(n)
4. Linearithmic O(n log n)
5. Quadratic O(n^2)
6. Cubic O(n^3)
Does the time requirement of polynomial-time or exponential-time algorithms grow
faster? - ANSW Exponential
When is the only time that exponential-time algorithms are practical? - ANSW For small
values of n
What is the complexity goal of an algorithm? - ANSW Polynomial-time with low growth
rate
What are the three growth rate notations? - ANSW Big O
Omega
Theta
Exam Review | A+ Verified Answers
What are the Software Development Life Cycle Models? - ANSW Waterfall
Agile
Spiral
V-Model
DevOps
List steps in waterfall model - ANSW 1. Analysis
2. Requirements specification
3. Design
4. Implementation
5. Testing and integration
6. Operation and maintenance
List components of technical documentation - ANSW 1. Hierarchical diagram / structure
chart
2. Procedure specification
3. Program listing
4. Test cases
6. Major problems encountered
7. Limitation of current works
What are the 3 Design strategies - ANSW 1. Top-down design
2. Bottom-up design
3. Stepwise refinement
What are the 3 types of parameters? - ANSW 1. Input parameters
2. Output parameters
3. Input-output parameters
What are the two types of testing (Include what they're also known as)? - ANSW 1.
Black-box (Function Testing)
2. White-box (Structural Testing)
Define Algorithm - ANSW A set of instructions for solving a problem in a finite number
of sets
Define Program - ANSW A particular implementation of an algorithm in a chosen
program language
, Algorithm analysis approaches - ANSW 1. Assess time and space recourse
requirements
2. Quantitative comparison (# of operations)
3. Best case, worst case, and average case analysis
4. Lower bound theory
5. Theory of NP-hard and NP-Complete
What is complexity? - ANSW The measure of how resource requirements of a program
or algorithm SCALE (time and space)
What are the typical growth rate functions (8 covered in notes) in order from most
efficient to least efficient? - ANSW 1. 1
2. log n
3. n
4. n log n
5. n^2
6. n^3
7. 2^n
8. n!
What are the two classes of algorithms based on growth rates? - ANSW 1. Polynomial-
time
2. Exponential-time
What are the 6 polynomial-time algorithms? (Bounded by polynomial in n degree) -
ANSW 1. Constant O(1)
2. Logarithmic O(log n)
3. Linear O(n)
4. Linearithmic O(n log n)
5. Quadratic O(n^2)
6. Cubic O(n^3)
Does the time requirement of polynomial-time or exponential-time algorithms grow
faster? - ANSW Exponential
When is the only time that exponential-time algorithms are practical? - ANSW For small
values of n
What is the complexity goal of an algorithm? - ANSW Polynomial-time with low growth
rate
What are the three growth rate notations? - ANSW Big O
Omega
Theta
